models/minimax/minimax-m2-1
M
minimax·active

MiniMax: MiniMax M2.1

minimax's efficiency model. Context window: 205K tokens.

Overall score
4.08
/5.00 · ranked #63
Input
$0.290
per 1M tokens
Output
$0.950
per 1M tokens
Context
205K
tokens
Blended
$0.785
3:1 out:in ratio

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Scores by test

Methodology →
Structured Output
4.0
Strategic Analysis
4.0
Constrained Rewriting
4.0
Creative Problem Solving
3.0
Tool Calling
5.0
Faithfulness
5.0
Classification
3.0
Long Context
4.0
Safety Calibration
4.0
Persona Consistency
5.0
Agentic Planning
4.0
Multilingual
4.0
Tabular Data
4.0

What you need to know

MiniMax M2.1 distinguishes itself through high reliability in execution and consistency. It achieves perfect scores in tool calling, faithfulness, and persona consistency, making it a strong candidate for agentic workflows where adherence to a specific identity and precise API interaction are critical.

The model offers a competitive price point with a blended cost of $0.785/MTok, providing high-end utility in structured output and strategic analysis at a mid-tier price. While it supports a 205K context window, its performance in long-context retrieval is slightly lower than its execution capabilities, suggesting it is more effective for precise task completion than massive document synthesis.

Performance dips in classification and creative problem solving, where it scores 3/5. This indicates a limitation in nuanced categorization and divergent thinking, meaning it is less suited for open-ended brainstorming or complex labeling tasks.

Use this model for building reliable AI agents, tool-integrated applications, or persona-driven interfaces. Skip this model for creative content generation or high-accuracy classification projects.

Strengths — Top 3

Tool Calling5.0/5.0
Faithfulness5.0/5.0
Persona Consistency5.0/5.0

Relative weaknesses — Bottom 3

Creative Problem Solving3.0/5.0
Classification3.0/5.0
Structured Output4.0/5.0

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